A multidimensional system is a system that exhibits behavior autonomously or as a function of multiple variables in response to a system input. A chaotic system is one that exhibits chaotic behavior (i.e., behavior characterized by random responses) during normal operation. The brain is an example of a multidimensional system that also exhibits chaotic behavior during normal operation. In a relatively significant percentage of the human population, the brain experiences periodic, abnormal episodes characterized by non-chaotic behavior. This abnormal behavior may be caused by a wide variety of conditions. Epilepsy is one of these conditions.
Epilepsy is a chronic disorder characterized by recurrent brain dysfunction caused by paroxysmal electrical discharges in the cerebral cortex. At any given time, Epilepsy affects approximately 50 million people worldwide. If untreated, an individual afflicted with epilepsy is likely to experience repeated seizures, which typically involve some level of impaired consciousness. Some forms of epilepsy can be successfully treated through medical therapy. However, medical therapy is less effective with other forms of epilepsy, including Temporal Lobe Epilepsy (TLE) and Frontal Lobe Epilepsy (FLE). With TLE and FLE, removing the portion of the hippocampus and/or cerebral cortex responsible for initiating the paroxysmal electrical discharges, known as the epileptogenic focus, is sometimes performed in an effort to control the seizures.
For quite some time, the medical community has attempted to develop techniques that provide seizure prediction and/or seizure warning, where seizure prediction will be understood to involve a long-range forecast of seizure-onset time, and seizure warning will be understood to involve a long-range indication of conditions conducive to an impending seizure. Any such technique would certainly have numerous clinical and non-clinical application. For example, in order to more effectively treat certain Epilepsy patients, such a technique might be used in conjunction with a device, perhaps an implanted device, designed to deliver a dosage of anti-seizure medication into the patient's bloodstream for the purpose of averting an impending seizure.
In another example, such a technique could be used during pre-surgical evaluations to assist in pinpointing the epileptogenic focus, which is to be removed during surgery. It is understood that during a seizure, blood flow to the epileptogenic focus significantly increases. If certain radio-labeled ligands are injected into the patient's bloodstream in a timely manner, it is possible to monitor that increased blood flow using radiography, thereby allowing a physician to accurately pinpoint the boundaries of the epileptogenic focus. A true seizure prediction and/or warning technique would provide an indication of an impending seizure well in advance and provide sufficient time to prepare for and administer, for example, the aforementioned radiography ligand.
One of the most important tools for evaluating the physiological state of the brain is the electroencephalogram (EEG). The standard for analyzing and interpreting an EEG is visual inspection of the graphic tracing of the EEG by a trained clinical electroencephalographer. However, there is no established method for predicting seizure onset or for providing a seizure warning well before seizure onset by visually analyzing an EEG. Moreover, the use of traditional signal processing techniques on EEG signals has likewise yielded little practical information. These traditional techniques are limited in their effectiveness because the brain is a multidimensional system that produces nonlinear signals with spatial as well as temporal properties. Thus, traditional signal processing techniques employing standard, linear, time series analysis methods cannot detect the spatio-temporal properties that are critical in providing effective seizure warning and prediction.
Commonly assigned U.S. Pat. No. 6,304,775, however, describes systems and methods capable of effectively generating true seizure warnings and predictions well in advance of impending seizures. The systems and methods described in this patent take advantage of the spatio-temporal characteristics exhibited by certain sites within the brain, when compared with the spatio-temporal characteristics exhibited by other sites within the brain, as these characteristics are noticeably different prior to an impending seizure as compared to the spatio-temporal characteristics exhibited by these same sites during seizure free intervals. In fact, these spatio-temporal characteristics may be noticeable hours, and in some cases, days before the occurrence of a seizure. As such, the systems and methods described in U.S. Pat. No. 6,304,775 use these differences as a seizure transition indicator.
U.S. Pat. No. 6,304,775 specifically describes, among other things, a technique that provides timely impending seizure warning (ISW), seizure susceptibility period detection (SSPD) and time to impending seizure prediction (TISP). The technique involves acquiring electrical or electromagnetic signals generated by the brain, where each signal corresponds to a single EEG electrode or channel. Each signal is pre-processed (e.g., amplified, filtered, digitized) and sampled. This results in a sequence of digital samples for each signal over a period of time, referred to therein as an epoch. The samples are then used to generate a phase space portrait for each signal epoch.
For each phase space portrait, a parameter reflecting rate of divergence is computed based on adjacent trajectories in the phase space, where rate of divergence, in turn, reflects the chaoticity level of the corresponding signal. In U.S. Pat. No. 6,304,775, the parameter that is used for this purpose is the short-term, largest Lyapunov exponent (STLMAX).
In general, the STLMAX values associated with each EEG signal (i.e., each EEG channel) are compared to the STLMAX values associated with each of the other channels. In U.S. Pat. No. 6,304,775, the comparisons are preferably achieved by applying a T-statistic, which results in a sequence of statistical values, or T-index values, for each channel pair, where a sequence of T-index values represents a level of correlation or entrainment between the spatio-temporal response associated with the two channels that make up each channel pair.
The technique, when first employed, goes through an initialization period. During this initialization period, a number of “critical” channel pairs is identified, where a critical channel pair is defined in U.S. Pat. No. 6,304,775 as a pair of channels that exhibits a relatively high level of entrainment (i.e., relatively low T-index values for a predefined period of time) prior to seizure onset.
During the initialization period, a patient may experience one or more seizures. After each, the list of critical channel pairs is updated. Eventually, the list of critical channel pairs is considered sufficiently refined, and the initialization period is terminated. Thereafter, the ISW, SSPD and TISP functions may be activated and the T-index values associated with the critical channel pairs are monitored and employed in generating timely ISWs, SSPDs and/or TISPs.
Even after the initialization period is over, the list of critical channel pairs is updated following each seizure. Updating the list is important because the brain does not necessarily reset itself completely after each seizure and because the physiological state of the patient may change over time. As a result, the spatio-temporal characteristics associated with any given channel may change over time. Thus, a channel pair previously identified as a critical channel pair may need to be removed from the list of critical channel pairs, while a channel pair that was not previously identified as a critical channel pair may need to be added to the list and subsequently used in generating a next ISW, SSPD or TISP.